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Source channel @githubtrending · Post #15062 · Aug 15

#python#mllm#point_clouds#scene_understanding#spatial_intelligence SpatialLM is a powerful 3D language model that turns complex 3D point cloud data from videos, RGBD images, or LiDAR into clear, structured 3D scene layouts showing walls, doors, windows, and objects with labels. It works without needing special equipment and can detect user-specified object categories. This helps you understand and analyze indoor spaces better, useful for robotics, navigation, and 3D design. You can run it on your data, visualize results, and even customize detection tasks easily, making 3D scene understanding more accessible and flexible for many applications. https://github.com/manycore-research/SpatialLM

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IELTS|Newspapers & Magazines｜English

@emagzinewspars · Post #9684 · 12/07/2025, 01:05 AM

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#The_Science🇺🇸📕[PDF]⬇️ 4 #December2025 #Weekly_Magazines For learning, for free(dom). @backupofmagazines This issue explores a century of quantum mechanics, where breakthroughs in quantum simulators, chemistry modeling, and information hardware illustrate how #QuantumTech and #AI innovation are reshaping modern science. As researchers revisit the Schrödinger equation’s legacy, new discoveries in DNA repair, materials design, and synthetic biology highlight cross-disciplinary shifts fueled by #FutureScience trends. With debates on #SciencePolicy and global collaboration, the issue captures a moment when #ResearchInnovation accelerates faster than ever, redefining both technology and our understanding of reality.

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